For nearly a decade, countries have been adopting artificial intelligence, machine learning and large language models on a large scale, showcasing their efficiency in managing complex tasks and significantly boosting productivity across corporate and government sectors. The Indian government is also positioning the economy to embrace AI, aiming for transformative growth in industries and public services. In January, the Ministry of Electronics and Information Technology (MeitY) released the "AI Governance Guidelines Development" report, emphasizing the need for a structured, responsible, and inclusive approach to unlocking AI's potential. The report's recommendations aim to establish a governance framework that fosters innovation while protecting societal and individual interests.

The report outlines a comprehensive strategy for AI governance in India, starting with the creation of an Inter-Ministerial AI Coordination Committee to unify government efforts, prevent fragmented approaches, and optimize resources. By involving industry and academic experts, the Committee aims to address risks like AI-driven discrimination and cybersecurity threats. A Technical Secretariat at MeitY would act as an operational hub, conducting horizon scanning and mapping stakeholders in India's AI ecosystem. These measures are designed to promote inter-ministerial collaboration, streamline regulations and align AI applications in sectors like healthcare, agriculture, and education with technological progress.

To enhance transparency, accountability and innovation, the report suggests creating an AI incident database for evidence-based policymaking and public trust. It also recommends tools like watermarking, platform labelling, and blockchain to trace AI outputs and combat issues like deepfakes. Lastly, the proposed Digital India Act (DIA) should include AI-specific provisions, such as improved grievance redress mechanisms and capacity-building for regulators. These initiatives are undoubtedly essential and timely. Kudos to MeitY for introducing the governance report at the right moment! However, a critical prerequisite is the development and maintenance of high-quality, industry-agnostic data to ensure the effective implementation and success of these efforts.

When discussing capacity building, clean and qualitative data emerges as an essential foundation for effective decision-making and sustainable development. Data serves as the backbone of modern governance, economic planning and technological advancement. However, India faces significant challenges in collecting, managing and utilizing such data effectively, creating critical gaps across various sectors. While global standards like the European Union’s General Data Protection Regulation (GDPR) have demonstrated how data can be protected and utilized responsibly, India lags far behind in creating and maintaining qualitative datasets. This shortfall not only limits the country's ability to leverage AI but also hampers its overall development trajectory.

The healthcare sector exemplifies the ramifications of inadequate data. High-quality, comprehensive datasets are crucial for implementing AI-driven solutions that can revolutionize healthcare delivery. In India, the lack of reliable data, particularly in rural and remote areas, restricts the deployment of AI for diagnostics, personalized treatment plans, and epidemic prediction. Without accurate health records and real-time data, public health initiatives struggle to address pressing issues such as maternal mortality, malnutrition, and non-communicable diseases. Similarly, climate change mitigation efforts face severe hurdles due to inconsistent and incomplete datasets. For instance, AI has the potential to analyses environmental patterns and recommend adaptive strategies, but this requires granular, spatial, and time series data on weather conditions, soil quality, and biodiversity—all of which remain fragmented or unavailable in India.

Similarly, in agriculture, the lack of accurate data on crop losses caused by droughts, floods, and pests has led to delays or inadequacies in compensating farmers. This, in turn, affects agricultural productivity and rural livelihoods. Moreover, the persistent issue of inadequate employment data remains a significant barrier to deploying AI effectively across industries. India’s unorganized sector, which accounts for perhaps more than 90% of the workforce of the entire secondary sector, is particularly underserved. Without accurate data on employment patterns and workforce dynamics, it is nearly impossible to implement AI-driven solutions that could optimize labor markets and enhance productivity.

The financial sector offers a glaring example of the consequences of inadequate data transparency. The 2018 collapse of Infrastructure Leasing & Financial Services (IL&FS) and the subsequent liquidity crunch in Non-Banking Financial Companies (NBFCs) revealed systemic weaknesses in data collection and risk assessment. The absence of clear and transparent data on financial transactions and institutional vulnerabilities not only destabilized the sector but also had ripple effects on industries dependent on NBFC financing, such as real estate and small-scale enterprises.

The government must prioritize the generation and maintenance of high-quality clean data to harness the full potential of AI technology effectively. India has an opportunity to harness the transformative potential of robust data systems. The Goods and Services Tax (GST) framework illustrates how data can be utilized effectively. GST-generated data provides insights into state-level manufacturing activities, inter-state mobility, and the pace of economic activity in specific regions. Such data not only enhances tax compliance but also informs policy decisions and fosters economic growth.

The bottom line is that clean and qualitative data is indispensable for India’s development. Addressing existing gaps in data collection and management is critical for enabling AI-driven innovations, improving governance, and ensuring equitable growth. By investing in data infrastructure and adopting best practices from global benchmarks, India can overcome its current limitations and unlock its full AI potential. Building on the above recommendations, MeitY, in collaboration with the Ministry of Statistics and Programme Implementation (MOSPI), can serve as the nodal agency responsible for maintaining high-quality data that accurately represents the diverse segments of Indian society.

If implemented effectively, the recommendations, supported by clean and high-quality data, could position India as a global leader in ethical AI development. However, the government must commit to substantial investments in AI, especially in light of China’s launch of DeepSeek, a wake-up call not just for India but for the world. As the global community watches India’s AI journey unfold, the nation has a unique opportunity to set a benchmark for responsible and impactful AI governance. The question is no longer whether India can lead in AI, but how it will achieve this leadership. The time to act is now.

Ankeetaa Mahesshwari is an Associate Fellow, and Abhishek Jha is a Fellow, at Pahle India Foundation, a New Delhi-based public policy think tank.